Echo detection with background noise based screening

ABSTRACT

An illustrative controller includes: a transmitter to drive the acoustic transducer to generate acoustic bursts; a receiver to sense a response of the acoustic transducer to echoes; and a processing circuit coupled to the transmitter and to the receiver, the processing circuit configured to convert said received response into output data by: correlating said response to a driving signal to obtain a correlation response; distinguishing peak areas from non-peak areas in said correlation response; deriving a noise level in a portion of said correlation response based on the non-peak areas within said portion; calculating a signal to noise ratio (SNR) for a peak signal within the portion as a ratio of a peak value for the peak signal to the noise level in said portion of said correlation response; and accepting the peak signal as an echo only if the SNR for said peak signal exceeds a predetermined threshold.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to provisional U.S. application63/127,599, filed 2020 Dec. 18 and titled “Ultrasonic Sensor System” byinventors M. Hustava, P. Kostelnik, and D. Bartos. The presentapplication further relates to U.S. application Ser. No. 16/530,654,filed 2019 Aug. 2 and titled “Ultrasonic Sensor Having Edge-Based EchoDetection” by inventors M. Hustava and J. Kantor. Both of the foregoingapplications are hereby incorporated herein by reference.

BACKGROUND

Modern automobiles are equipped with an impressive number and variety ofsensors. For example, cars are now routinely equipped with arrays ofultrasonic sensors to monitor distances between the car and any nearbypersons, pets, vehicles, or obstacles. Due to environmental “noise” andsafety concerns, each of the sensors may be asked to provide tens ofmeasurements each second while the car is in motion. It is important forsuch sensor arrays to perform reliably, even in environments that changein complex ways. Seemingly small differences, such as the presence orabsence of a curb, or even the difference between paved and gravelsurfaces, can significantly change the characteristic reflection of apole, bollard, or other slim obstacle.

The noise encountered by park-assist sensors is known to have differentorigins, and includes for instance pneumatic noise such as vibrationsoriginating from other vehicles operating nearby; ultrasound from othersources such as sensors on other cars, parking lot occupation detectors,and traffic light control systems; cross-correlation noise betweendifferent frequency bands; and so on. There is therefore a need foradequate handling of such noise in the detection and evaluation of anyreceived ultrasound signals.

SUMMARY

Accordingly, there are disclosed controllers for acoustic transducers,park assist control systems, and methods providing echo detection withbackground noise based screening. One illustrative controller includes:a transmitter to drive the acoustic transducer with a driving signal togenerate acoustic bursts; a receiver to sense a response of the acoustictransducer to echoes of each acoustic burst; and a processing circuitcoupled to the transmitter and to the receiver, the processing circuitconfigured to convert said received response into output data by:correlating said response to said driving signal to obtain a correlatedmagnitude signal; distinguishing peak areas from non-peak areas in saidcorrelated magnitude signal; deriving a noise level in a portion of saidcorrelated magnitude signal based on the correlated magnitude signal innon-peak areas within said portion; calculating a signal to noise ratio(SNR) for a peak signal within the portion as a ratio of a peak valuefor the peak signal to the noise level in said portion of saidcorrelated magnitude signal; and accepting the peak signal as an echoonly if the SNR for said peak signal exceeds a predetermined threshold.

An illustrative park assist control system includes a microcontroller,at least one a controller for an acoustic transducer, and acommunication bus coupling the microcontroller and said at least onecontroller. The controller includes: a transmitter to drive the acoustictransducer with a driving signal to generate acoustic bursts; a receiverto sense a response of the acoustic transducer to echoes of eachacoustic burst; a processing circuit coupled to the receiver to convertsaid received response into output data; and an interface to convey saidoutput data over the communication bus. At least one of the processingcircuit and the microcontroller is configured to: correlate saidresponse with a pulse pattern to obtain a correlated response;distinguish peak areas from non-peak areas in said correlated response;derive a noise level in a portion of said correlated response using onlythe non-peak areas within said portion; calculate a signal to noiseratio (SNR) for a peak signal within the portion as a ratio of a peakvalue for the peak signal to said the noise level; and accept the peaksignal as an echo only if the SNR for said peak signal exceeds apredetermined threshold.

An illustrative method of operating a piezoelectric-based sensorincludes: driving a piezoelectric transducer to generate a burst ofacoustic energy; obtaining a response from the piezoelectric transducer;correlating said response relative to said driving signal to obtain acorrelated response; distinguish peak areas from non-peak areas in saidcorrelated response; deriving a noise level in a portion of saidcorrelated response using only the non-peak areas within said portion;calculating a signal to noise ratio (SNR) for a peak signal within theportion as a ratio of a peak value of for the peak signal to the noiselevel; and accepting the peak signal as an echo only if the SNR for saidpeak signal exceeds a predetermined threshold.

Another illustrative controller for an acoustic transducer includes: atransmitter drive the acoustic transducer with a driving signal togenerate acoustic bursts; a receiver to sense a response of the acoustictransducer to echoes of each acoustic burst; a processing circuitcoupled to the transmitter and to the receiver, the processing circuitconfigured to convert said received response into output data by:correlating said response to said driving signal to obtain a correlatedresponse; distinguishing peak areas from non-peak areas in saidcorrelated response; using the non-peak areas in a portion of thecorrelated response to derive a noise level; calculating a signal tonoise ratio (SNR) for a peak signal within the portion as a ratio of apeak value for the peak signal to the noise level; and identifying thepeak signal as a ground reflection if the SNR falls below apredetermined threshold.

Each of the foregoing examples can be employed individually or inconjunction, and may include one or more of the following features inany suitable combination: 1. using the processing circuit ormicrocontroller to determine a derivative signal from the correlatedmagnitude signal, and to accept the peak signal as an echo only if thederivative signal corresponding to said peak signal exceeds a derivativethreshold. 2. the derivative threshold is a CFAR threshold determinedfrom a Continuous False Alarm Rate (CFAR) algorithm applied to thederivative signal. 3. a memory for storing the derivative threshold. 4.calculating a CFAR threshold using a Continuous False Alarm Rate (CFAR)algorithm, and comparing the correlated magnitude signal with said CFARthreshold to distinguish the peak areas from non-peak areas. 5.accepting the peak signal as an echo only if the peak signal is withinone of said peak areas. 6. the processing circuit includes a peakmeasurement element to detect said peak value. 7. providing an outputindicating a presence of a ground reflection. 8. the output indicativeof ground reflections is based on the calculated SNR ratio.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an overhead view of an illustrative vehicle equipped withparking-assist sensors.

FIG. 2 is a block diagram of an illustrative parking assist system.

FIG. 3 is a circuit schematic of an illustrative parking-assist sensor.

FIGS. 4A and 5A show graphs of illustrative signal curves for areference technology.

FIGS. 4B and 5B show graphs of illustrative signal curves for thepresent technology.

FIG. 6 is a block diagram of a first illustrative processing circuit.

FIG. 7 is a block diagram of a second illustrative processing circuit.

FIG. 8 is a block diagram of a third illustrative processing circuit.

FIG. 9 is a block diagram of a fourth illustrative processing circuit.

FIG. 10 is a block diagram of a fifth illustrative processing circuit.

DETAILED DESCRIPTION

It should be understood that the drawings and following description donot limit the disclosure, but on the contrary, they provide thefoundation for one of ordinary skill in the art to understand allmodifications, equivalents, and alternatives falling within the scope ofthe claim language.

As an illustrative usage context, FIG. 1 shows a vehicle 102 equippedwith a set of ultrasonic parking-assist sensors 104. The number andconfiguration of sensors in the sensor arrangement varies, and it wouldnot be unusual to have six sensors on each bumper with two additionalsensors on each side for blind-spot detectors. Some contemplated sensorarrangements include 24 ultrasonic sensors arranged around the vehicle.The vehicle may employ the sensor arrangement for detecting andmeasuring distances to objects in the various detection zones,potentially using the sensors for individual measurements as well ascooperative (e.g., triangulation, multi-receiver) measurements.

The ultrasonic sensors are transceivers, meaning that each sensor cantransmit and receive bursts of ultrasonic sound. Emitted burstspropagate outward from the vehicle until they encounter and reflect froman object or some other form of acoustic impedance mismatch. Thereflected bursts return to the vehicle as “echoes” of the emittedbursts. The times between the emitted bursts and received echoes areindicative of the distances to the reflection points. In many systems,only one sensor transmits at a time, though all of the sensors may beconfigured to measure the resulting echoes. However multiplesimultaneous transmissions can be supported through the use oforthogonal waveforms or transmissions to non-overlapping detectionzones.

While the parking-assist system context is used as an example herein,the concepts of this disclosure may be applied to any type of obstaclemonitoring, and may be particularly suitable for those that prioritizesreliability and rapid response. In order to mitigate any tradeoffbetween reliability and extended detection range, appropriate modulationcan be added to the transmit pulse to resolve the disadvantages ofincreasing the length of the transmit pulse. Subsequently, a correlatormay be used to shorten or compress the echo of a longer, modulatedtransmit pulse.

In various embodiments, use is made of chirp-modulated signals. A chirpis a transmit pulse that changes frequency during transmission. One formof modulation of the transmit pulse is, for instance, a linear frequencymodulated (“LFM”) chirp. An up-chirp is a chirp that increases infrequency during transmission, and a down-chirp is a chirp thatdecreases in frequency during transmission. For clarity, the examplesused herein will consider a linear increase or decrease, however invarious embodiments the increase or decrease is not linear. Avariable-rate chirp increases and decreases in frequency at differentrates during the pulse. A correlator can compress the echo of a chirpwithout introducing much or any correlation noise. As such, peakdetection of the echo is facilitated without decreasing time resolution.Additionally, LFM chirps withstand Doppler frequency shift without, orwith a minimum of, increase in correlation noise. LFM chirps can be usedas transmit pulses for measuring a distance to an obstacle, or object,situated in front of a sensor system.

For sake of clarity, the term ‘pulse’ as used herein refers to a singledriving signal in a series of driving signals. Such a chirp pulse mayhave a long duration in comparison to an amplitude modulated (AM)signal, for instance more than 1 millisecond, such as in the range of2-3 milliseconds.

FIG. 2 shows an electronic control unit (ECU) 202 coupled to the variousultrasonic sensors 204 as the center of a star topology. Of course,other topologies including serial, parallel, and hierarchical (tree)topologies, are also suitable and contemplated for use in accordancewith the principles disclosed herein. To provide automated parkingassistance, the ECU 202 may further connect to a set of actuators suchas a turn-signal actuator 206, a steering actuator 208, a brakingactuator 210, and throttle actuator 212. ECU 202 may further couple to auser-interactive interface 214 to accept user input and provide adisplay of the various measurements and system status. Using theinterface, sensors, and actuators, ECU 202 may provide automatedparking, assisted parking, lane-change assistance, obstacle andblind-spot detection, and other desirable features.

One potential sensor configuration is now described with reference toFIG. 3, which shows a three-terminal configuration with two terminalsfor power and one terminal for I/Q Other communication and power supplytechniques such as those provided in the DSI3, LIN, and CAN standards,would also be suitable and are contemplated for use in accordance withthe principles disclosed herein. Besides the two power terminals (Vbatand GND) shown in the embodiment of FIG. 3, each of the illustrativeultrasonic sensors is only connected to the ECU 202 by a singleinput/output (“I/O” or “IO”) line. The I/O line may be biased to thesupply voltage (the “de-asserted” state) by a pull-up resistor when itis not actively driven low (the “asserted” state) by the ECU 202 or bythe sensor controller 302. The communication protocol is designed tohave only one of the two controllers (ECU 202 or sensor controller 302)asserting the I/O line at any given time.

The sensor controller 302 includes an I/O interface 303 that, whenplaced in a recessive mode, monitors the I/O line for assertion by theECU 202 and, when placed in a dominant mode, drives the state of the I/Oline. The ECU communicates a command to the sensor by asserting the I/Oline, the different commands being represented by assertions ofdifferent lengths. The commands may include a “send and receive”command, a “receive only” command, and a “data mode” command.

The sensor controller 302 includes a core logic 304 that operates inaccordance with firmware and parameters stored in nonvolatile memory 305to parse commands from the ECU and carry out the appropriate operations,including the transmission and reception of ultrasonic bursts. Totransmit an ultrasonic burst, the core logic 304 is coupled to atransmitter 306 which, with a suitably modulated local oscillator signalfrom a voltage controlled oscillator 307, drives a set of transmitterminals on the sensor controller 302. The transmitter terminals arecoupled via a transformer M1 to a piezoelectric element PZ. Thetransformer M1 steps up the voltage from the sensor controller (e.g., 12volts) to a suitable level for driving the piezoelectric element (e.g.,tens of volts). The piezoelectric element PZ has a resonance frequencythat can be tuned with external components such as with a parallelcapacitor C3, and has a resonance quality factor (Q) that can similarlytuned, e.g., with a parallel resistor R1.

As used herein, the term “piezoelectric transducer” includes not onlythe piezoelectric element, but also the supporting circuit elements fortuning, driving, and sensing, the piezoelectric element. In theillustrative embodiment, these supporting elements are the transformerM1, the tuning resistor and tuning capacitor, and the DC-isolationcapacitors. Optionally, output and input capacitance of the transmitter306 and amplifier 308, respectively, may also be included as parasiticcharacteristics of the supporting circuit elements considered to be partof the transducer. However, the use of the term “piezoelectrictransducer” does not necessarily require the presence of any supportingcircuit elements, as a piezoelectric element may be employed alonewithout such supporting elements. In the illustrated embodiment, a pairof DC-isolation capacitors C1, C2 couple the piezoelectric element tothe sensor controller's pair of receive terminals to protect againsthigh voltages. Further protection is provided with internal voltageclamps on the receive terminals. Such protection may be desired for theintervals when the piezoelectric element is transmitting.

Commands received via the I/O line trigger the core logic 304 to operatethe transmitter and receiver and to provide the measurement results tothe ECU 202 via the I/O line, also referred herein as a communicationbus. The measurement results are herein also referred to as output data.A preferred communication bus is the DSI3 bus, although othercommunication buses such as LIN, SENT, CAN are not excluded. The corelogic 304 may monitor other sensor conditions such as having the supplyvoltage “under-voltage” or “over-voltage” while transmitting anultrasonic burst, thermal shutdown of transmitter, a hardware error, anincomplete power-on reset, or the like. The core logic 304 may detectand classify multiple such transducer fault states and error conditions,storing the appropriate fault codes in internal registers or nonvolatilememory 305.

As the received echo signals are typically in the millivolt or microvoltrange, a front-end amplifier 308 amplifies the signal from the receiveterminals. A mixer 309 multiplies the amplified receive signal with thelocal oscillator signal to down convert the modulated signal tobaseband, which is then digitized by an analog-to-digital converter(ADC) and processed in a digital signal processor (DSP) 310.Alternatively, the receive signal can be digitized beforedownconversion, in which case the mixer 309 may be anin-phase/quadrature (I/O) digital mixer 303, giving Zero IntermediateFrequency (ZIF) IQ data as its output. (Though the term “ZIF” is usedherein, the downconverted signal may in practice be a low intermediatefrequency or “near-baseband” signal.)

DSP 310 applies programmable methods to monitor the piezoelectrictransducer during the transmission of a burst, and to detect any echoesand measure their parameters such as time-of-flight (ToF), duration, andpeak amplitude. Such methods may employ threshold comparisons, minimumintervals, peak detections, zero-crossing detection and counting, noiselevel determinations, and other customizable techniques tailored forimproving reliability and accuracy. The DSP 310 may further process theamplified receive signal to analyze characteristics of the transducer,such as resonance frequency and quality factor, and may further detecttransducer fault states.

In one embodiment the DSP comprises a digital filter that is configuredto cooperate with a memory for storing finite impulse response (FIR)filter coefficients. As mentioned above, the mixer 309 is in oneembodiment a quadrature mixer. This I/Q digital mixer 309 has an inputconnected to the output of analog-to-digital converter, an input forreceiving a mixing signal FTX, and first and second outputs forproviding an in-phase signal and a quadrature signal, respectively, thatcorresponds to an amplitude and a phase of the signal input from theacoustic transducer in the complex plane.

As mentioned above, the mixer 309 is in one implementation a quadraturemixer. This I/Q digital mixer 309 has an input connected to the outputof an analog-to-digital converter (not shown), an input for receiving amixing signal Frx, and first and second outputs for providing anin-phase signal and a quadrature signal, respectively, that correspondsto an amplitude and a phase of the signal input from the acoustictransducer in the complex plane. The DSP may include one or more digitalfilters that are configured to retrieve and use filter coefficientsstored in memory for operating on the ZIF-IQ signal. More particularly,the digital filters may include low-pass filters and correlators. Evenmore specifically, at least one correlation filter has coefficients thatmatch the shape of the transmit pulse at baseband, such that the filteroutput exhibits a peak wherever an echo appears in the downconvertedreceive signal.

The DSP may further include programmable modules or dedicated circuitryfor other operations, including phase derivation, magnitude measurement,down sampling, amplitude scaling (attenuation control), noisesuppression, peak detection, reverberation monitoring, and transducerdiagnostics, and an interface for host communications. A magnitudedetector module or circuit operates on the digitized and downconvertedreceive signal, combining the in-phase and quadrature signal componentsto output a magnitude signal.

In operation of one illustrative implementation, if an object reflectsthe transmit pulse, the piezoelectric transducer supplies a receivesignal that includes the echo of the chirp signal as the input signal atI/Q digital mixer 309. Once any residual reverberation from the transmitpulse is finished, a chirp echo signal can be detected for near rangeobject detection. I/Q digital mixer 309 shifts the receive signal to sumand difference frequencies, in which the difference frequency is atbaseband (zero frequency). I/Q digital mixer 309 outputs both anin-phase signal component and a quadrature phase signal component of thereceived signal. One or more correlators receive the in-phase andquadrature signal components and produce a correlation signal having apeak where the receive signal contains an echo of the transmit pulse.Two correlators may be used for dual-channel operation, with a highchannel correlator for detecting high-channel chirps and a low channelcorrelator for detecting low-channel chirps.

In practice, the response as received and digitized does not merelyinclude any reflection from the ranging signal emitted by the acoustictransducer, but also includes noise. Such noise originates from avariety of potential sources. Part of the noise is periodical with themeasurement sequence and thus is repeatedly obtained as part of theresponse. This periodical noise may be electrical, acoustical,structural or processing noise. Examples of processing noise includeauto-correlation noise (i.e. within a single channel, such as chirp andAM) and cross-correlation noise (between different measurementchannels). One source of disturbing noise is noise due to groundreflections of the acoustic burst, i.e. reflections from the ground orsoil or road on which the car stands or drives in which the sensor isincorporated. Such ground reflections tend to be received relativelyshortly after the residual reverberations dies out. However, the momentof reception, the number of reflections, and the signal strength ofground reflections, each appears to depend on the type of ground.Furthermore, there may be real echo signals hidden between the groundreflections that should not be removed. A further source of disturbingnoise is found to occur in systems employing data compression to conveysensor signals to the ECU for processing. This noise may be classifiedas compression noise and may again give rise to fake echoes, i.e.signals with a signal strength comparable or even larger than that of asignal representing an echo, but still being due to noise only.

FIGS. 4A and 5A show two illustrative correlation magnitude curves(“MAGN”) that have been processed as described in incorporated U.S.application Ser. No. 16/530,654 (“Ultrasonic Sensor Having Edge-BasedEcho Detection”) to perform edge-based echo detection. Morespecifically, the processor(s) have processed the correlation magnitudeto detect falling edges where the magnitude exceeds a CFAR threshold andthe (negative) derivative exceeds a threshold values, yielding the curvelabeled “EDGE”. Where the falling edge is detected with a correlationmagnitude above a time-dependent threshold, the processor(s) assert anecho detection signal (“ECHO”), to be transmitted as a pulsed outputsignal to an ECU or as otherwise encoded echo information.

The detected echoes in these figures include ground reflections (namely,the echoes detected before 16 milliseconds), which may be undesirablefor most parking assistance systems. Of course it is possible forreflections from real obstacles to appear here too, so it is desirableto distinguish such reflections from ground reflections. Accordingly,there are provided herein improved methods for distinction of realechoes from fake echoes, as well as improved controllers with aprocessing circuit configured to perform such methods. The methods andcorresponding controllers may be configured to provide signalsindicative for the presence and/or type of ground reflections. Suchsignals may be provided in any suitable format from the controller tothe ECU.

FIG. 6 is a block diagram of a processing circuit according to a firstembodiment of the present technology. FIGS. 7 to 10 show correspondingprocessing circuits according to further embodiments of the presenttechnology. Equal reference numerals in these figures correspond toidentical or corresponding parts. It is observed that the block diagramsare schematic in nature and simplified to omit features not immediatelyrelevant for disclosing the present technology. For instance, thespecific processing of the channels, such as chirp channels, is notspecified herein. An example of a block diagram specifying processing ofchirp channels is for instance disclosed in U.S. application Ser. No.16/378,722, filed Apr. 9, 2019 and titled “Acoustic distance measuringcircuit and method for low frequency modulation (LFM) chirp signals” byinventors Marek Hustava and Tomas Suchy, which is hereby incorporatedherein by reference. A typical processing circuit may however includemore functions, such as for instance elucidated in FIG. 4 and thecorresponding description of U.S. application Ser. No. 16/724,783, filedDec. 23, 2019 and titled “Piezoelectric transducer controller havingmodel-based sideband balancing” by inventors Tomas Suchy, Jiri Kantor,and Marek Hustava, which is hereby incorporated herein by reference.

The illustrative block diagram of FIG. 6 shows a mixer 602 fordownconverting the signal received from the piezoelectric transducer(RECV) to baseband, a correlation filter 604 that convolves thedownconverted signal with the transmit pulse shape to produce acorrelation signal. (Multiple filters or multiple sets of filtercoefficients may be used to provide separate correlation signals forupper and lower sideband signals). A magnitude element 606 determinesthe absolute value of the correlation signal, or in some alternativeembodiments, squares the correlation signal, yielding a correlationmagnitude or energy signal that is supplied to various other elementsfor processing to detect peaks indicating reflections of transmit pulseenergy (echoes) from obstacles.

A CFAR element 608 operates on the correlation magnitude or energysignal to provide a CFAR Threshold (CT) signal in accordance with aConstant False Alarm Rate (CFAR) algorithm. Various CFAR algorithms aredescribed in the literature, including previously incorporated U.S.application Ser. No. 16/530,654, filed 2019 Aug. 2 and titled“Ultrasonic Sensor Having Edge-Based Echo Detection” by inventors M.Hustava and J. Kantor (citing U.S. Pat. No. 5,793,326 (“Hofele”)).Suitable CFAR algorithm variations include for instance CASH-CFAR (CellAveraging Statistic Hofele CFAR) and Ordered Statistic-CFAR (OS-CFAR).Briefly stated, the CFAR algorithms perform statistical processingwithin a moving window to determine a threshold value representingbackground “clutter”, the processing operating to exclude from thethreshold determination any strong peaks that would likely represent avalid echo. The CFAR variations vary in the precise nature of thestatistical processing, e.g., whether using a min-max-sum, rankordering, or averaging operations in combination with suitable weightingor scaling to enable adequate distinguishing between valid echoes andbackground noise. Various parameters of the algorithm (e.g., block size,window size) can be adjusted to optimize the adaptiveness of thethreshold. A CFAR offset value may be stored in a memory and added tothe algorithm-based threshold value to provide further tuning of the CTsignal.

The CFAR element 608 may operate on a symmetric or asymmetric windowaround a “current” sample of the correlation magnitude signal. A delayelement 609 may accordingly be used to provide a suitable time offsetbetween the “early” correlation magnitude signal supplied to the CFARelement 608 and the “current” correlation magnitude signal supplied tothe other elements of the processing circuit. A comparator 610 comparesthe current correlation magnitude signal to the CFAR threshold signal,asserting a selection signal for multiplexer 612 to indicate when thecorrelation magnitude signal is above the threshold (a “peak area”), andde-asserting the selection signal to indicate when the correlationmagnitude signal is below the threshold (a “non-peak area”). A noiseaveraging block 614 receives the selection signal at an inverted enable(/EN) input, also known as a disable input, that disables operation ofthe noise averaging block 614 while the comparator output is asserted.In this fashion, averaging block operates on the non-peak areas of thesignal and ignores the peak areas of the correlation magnitude signal.

In accordance with the present technology, the noise level is calculatedin noise level calculator 614 on the basis of signals in the correlationmagnitude signal outside a peak area only. Noise averaging block 614calculates an average within a given portion or moving window of thenon-peak correlation magnitude signal. As one example, a separateaverage is calculated for each portion of the magnitude signal. Thelength of the signal portion or moving window is suitably predefinedand/or controllable, for instance under control of a microcontroller(ECU). The noise averaging block 614 may be provided with a clock signalso as to define the length of a magnitude signal portion. A length of asignal portion is for instance in one advantageous implementation 0.1-10ms, or for instance 0.5-5 ms, such as 1˜4 ms or 2.5-3.0 ms. Theaveraging block may for instance be configured to sum signals of thenon-peak areas in the signal portion and divide it by the duration ofthe non-peak areas of the signal portion. While the present applicationrefers to an average, it is to be understood that the resulting averagemay be any type of average as known to the person skilled in the art,including the median, the arithmetic average (mean), the mode, thegeometric mean and/or a weighted average, and exponential rollingaverage.

For each peak in the current correlation magnitude signal, a peakmeasurement element 618 determines the signal strength by identifyingthe peak value (local maximum). A signal-to-noise ratio (SNR) block 616accepts each peak value from peak measurement element 618 and uses acorresponding noise average value from noise averaging block tocalculate a SNR value for that peak. We note here that block 616 is notlimited to any definitional formula such as SNR=20 log₁₀(signal/noise).In fact, given the hardware complexity typically associated with alogarithmic calculation, it may be preferred to use a simple ratio orother calculation that monotonically relates to the definitional formulain the region of interest. A comparator 620 compares the SNR value to apredetermined SNR threshold (ST) value, asserting an echo detectionsignal only when the SNR value for the peak exceeds the threshold.Though not shown here, the output of peak measurement element 618 mayalso be output from the sensor when the echo detection signal isasserted.

In the event that information concerning ground reflections is desired,such information may be obtained as the peak signals identified withoutassertion of the echo detection signal. Specific alternativeimplementations, including a separate comparator for the informationconcerning ground reflections, are not excluded.

FIG. 7 is a block diagram of a second embodiment of a processing circuitaccording to the present technology. This second embodiment differs fromthe first embodiment shown in FIG. 6, in that a further criterion isapplied so as to exclude false echoes. The further criterion is based onevaluation of derivative signals from the correlated response. Aderivation block 722 determines the time-derivative of the correlationmagnitude signal. One potential implementation is described in, e.g.,incorporated application Ser. No. 16/530,654 (“Ultrasonic sensor havingedge-based echo detection”). A comparator 724 compares the derivativesignal to a predetermined derivative threshold (DT) value. In thepresent example, the threshold is taken from memory, but it couldalternatively be calculated on the basis of one or more values in thememory. The output signal is transmitted to a logical AND block 726,which asserts an echo detection signal only when the derivative exceedsDT and the peak SNR exceeds ST (indicated by the assertion of the outputof comparator 620). A second delay element 709 is included within thederivative calculation path to provide a suitable time offset thataccounts for the CFAR element delay and the SNR determination delay, sothat the inputs to logical AND block 726 correspond to the same givensample of the correlation magnitude signal.

Hence, any pulsed output from the comparator 620 is only accepted if thederivative signal exceeds a threshold in comparator block 724. Thissecond criterion is based on the observation that rising edges and/orfalling edges of a valid echo peak are readily discernable, enabling theborders of an echo to be identified rather precisely. Thus, an echostart may be detected when the derivative signal raises above apredefined edge threshold. An echo end will be detected when thederivative signal falls below another predefined edge threshold. Hence,any signal with a peak level above a SNR ratio threshold but lacking asuitably-shaped correlation magnitude peak is still rejected. Althoughnot shown in the one of the figures, it is not excluded that the risingand falling edges may be used so as to distinguish peak areas from otherareas instead and/or in addition to the comparator 610.

FIG. 8 is a block diagram of a third embodiment of a processing circuitaccording to the present technology. It is similar to the embodiment ofFIG. 6, but comparator 610 is further linked to a multiplexer 812 on theprimary signal path to suppress non-peak portions of the correlationmagnitude signal and pass only the peak portions of the correlationmagnitude signal to the peak measurement block 616. The peakmeasurements provided by the peak measurement block 618, andcorrespondingly, the SNR measurements generated by block 616, are thusonly for those peaks exceeding the CFAR threshold. As before, comparator620 asserts an echo detection signal only when the calculated SNR exceedthe SNR threshold.

FIG. 9 shows a block diagram of a fourth embodiment of a processingcircuit according to the present technology. As with the previousembodiments, comparator 610 disables the noise averaging block 614 whenthe correlation magnitude signal exceeds the CFAR threshold. As with theembodiment of FIG. 7, a derivation block 722 determines the timederivative of the correlation magnitude signal, and comparator 724detects when the (rising or falling) edge derivative exceeds athreshold. Rather than gating the output of comparator 620, however, thederivative comparator 724 controls primary path multiplexer 912 to passthe correlation magnitude signal only when the derivative criterion issatisfied and to suppress the correlation magnitude signal otherwise. Itmay be appropriate that the result of the comparator 724 is firstconverted into pulses, so as to specify the duration of the echo peak.The peak measurement block 618, and correspondingly the SNR calculationblock 616, operate only on peaks having the requisite rising and/orfalling edge definition. Comparator 620 asserts the echo detectionsignal when the calculated SNR value exceed the SNR threshold.

While FIGS. 7 and 9 indicate that a derivation is calculated in block722 from a correlated magnitude signal, it is not excluded that aderivative signal is provided as a separate input, e.g., from a separatecorrelator or separate calculation thereof. Preferably, the derivativethreshold used in comparator 724 is derived from a CFAR algorithmadapted to determine a suitable derivative threshold.

FIG. 10 shows a fifth embodiment combining features of FIGS. 8 and 9.The primary signal path includes a multiplexer 812 controlled bycomparator 810 to pass only peak areas of the signal, and furtherincludes a multiplexer 912 controlled by derivative comparator 724 topass only those peaks satisfying the derivative criterion. The peakmeasurement block 618, and thus SNR block 616, accordingly operate onlyon those peaks satisfying the CFAR and derivative criteria, andcomparator 620 asserts the echo detection signal only when the SNRcriterion is satisfied.

FIGS. 4B and 5B show echo detection results using the CFAR, derivative,and SNR criteria, indicating the suppression of (most) false echoes thatwere not suppressed in the reference technology. As such, sensingmethods and controllers employing the SNR criterion provide a morereliable output. Furthermore, by reducing the number of false echoes,possibly to zero, the total number of detected echoes decreases,reducing the volume of data that may need to be transmitted from thesensor to the ECU over a limited bandwidth bus. The data volumereduction may advantageously reduce measurement delays, along withcommensurate increases in measurement repetition time and latency. Suchadvantages may be magnified in higher bandwidth buses supportingmultiple sensors.

It is further noted that the present technology advantageously screensfalse echoes that may be attributable to compression noise. Morespecifically, it is noted that some park assist sensing systems compressraw data, for instance Zero Intermediate Frequency (ZIF) IQ data,correlation magnitude data, and/or time-of-flight (ToF) data, forconveyance from the sensor controller to the microcontroller or ECU. Thecompression may lead to noise that some systems incorrectly interpret asechoes. The SNR criterion, optionally in combination with the CFAR andderivative criteria, enables the screening of such false echoes

Note that the disclosed processing and processing circuitry can beimplemented in the sensor controller, and that alternatively, at leastsome of the disclosed processing and processing circuitry may beimplemented in the ECU or microcontroller that receives raw data fromthe sensor controller. Where the processing is implemented by the sensorcontroller, it is contemplated that the excluded peaks potentiallyindicative of ground reflections may nevertheless be at leastintermittently conveyed to the ECU. Alternatively, the excluded peakspotentially representing ground reflections may be compared to storedreference signals and, if a suitable match is found, suitable signalindicating the presence and/or type of ground reflections may beconveyed to the ECU. Other data conveyed to the ECU may include dataspecifying the noise level, and/or data specifying locations of fallingand rising edges such as obtained in the analysis by means of derivationbased processing.

It is a further potential advantage of the present technology that thenecessary size of memory on or linked to the controller may be reduced.The separate removal of ground reflections enables the CFAR algorithm tobe performed with reduced memory buffering than what would otherwise beneeded. The CFAR memory buffering depends at least partially on thenumber of echo peaks to be stored in said memory. It has been found thatthe number of echo peaks to be stored can be lower than 30, preferablylower than 25, or more preferably 20 or less or even 15 or less. Evenwith 10 stored echo peaks or less, acceptable results may be achieved.

Though the operations shown and described above are treated as beingsequential for explanatory purposes, in practice the process may becarried out by multiple integrated circuit components operatingconcurrently and perhaps even speculatively to enable out-of-orderoperations. The sequential discussion is not meant to be limiting.Further, the foregoing description has presumed the use of an I/O linebus, but other bus embodiments including LIN, CAN and DSI3 arecontemplated. These and numerous other modifications, equivalents, andalternatives, will become apparent to those skilled in the art once theabove disclosure is fully appreciated. For example, correlated magnitudesignal may be determined by squaring the correlation filter output or bydropping the sign bit of a binary number representation. It is intendedthat the following claims be interpreted to embrace all suchmodifications, equivalents, and alternatives where applicable.

While dependent claims are written down to refer back to a single claimas a matter of claim drafting prescriptions in certain countries, it isobserved that any combination of a dependent claim with any of itspreceding claims is foreseen by the present inventors and is deemedincluded in the full disclosure of the present application. Furthermore,it is to be understood that the dependent claims specified for one claimcategory apply also to another claim category, but have merely beenomitted for the sake of limiting the overall number of claims and anyclaim fees that may be due as a result thereof.

1. A controller for an acoustic transducer, the controller comprising: atransmitter to drive the acoustic transducer with a driving signal togenerate acoustic bursts; a receiver to sense a response of the acoustictransducer to echoes of each acoustic burst; a processing circuitcoupled to the transmitter and to the receiver, the processing circuitconfigured to convert said received response into output data by:correlating said response to said driving signal to obtain a correlatedmagnitude signal; distinguishing peak areas from non-peak areas in saidcorrelated magnitude signal; deriving a noise level in a portion of saidcorrelated magnitude signal based on the correlated magnitude signal innon-peak areas within said portion; calculating a signal to noise ratio(SNR) for a peak signal within the portion as a ratio of a peak valuefor the peak signal to the noise level in said portion of saidcorrelated magnitude signal; and accepting the peak signal as an echoonly if the SNR for said peak signal exceeds a predetermined threshold.2. The controller as claimed in claim 1, wherein the processing circuitis further configured to: determine a derivative signal from thecorrelated magnitude signal; accept the peak signal as an echo only ifthe derivative signal corresponding to said peak signal exceeds aderivative threshold.
 3. The controller as claimed in claim 2, whereinthe derivative threshold is a CFAR threshold determined from aContinuous False Alarm Rate (CFAR) algorithm applied to the derivativesignal.
 4. The controller of as claimed in claim 2, further comprising amemory for storing the derivative threshold.
 5. The controller asclaimed in claim 1, wherein said distinguishing the peak areas fromnon-peak areas comprises calculating a CFAR threshold using a ContinuousFalse Alarm Rate (CFAR) algorithm, and comparing the correlatedmagnitude signal with said CFAR threshold.
 6. The controller as claimedin claim 5, wherein the processing circuit is further configured to:accept the peak signal as an echo only if the peak signal is within oneof said peak areas.
 7. The controller as claimed in claim 1, wherein theprocessing circuit further comprises a peak measurement element todetect said peak value.
 8. The controller as claimed in claim 1, whereinthe processing circuit is further configured to provide an outputindicating a presence of a ground reflection.
 9. The controller asclaimed in claim 8, wherein the processing circuit is configured togenerate said output indicative of ground reflections using thecalculated SNR ratio.
 10. A park assist control system, comprising amicrocontroller, at least one a controller for an acoustic transducer,and a communication bus coupling the microcontroller and said at leastone controller, the controller comprising: a transmitter to drive theacoustic transducer with a driving signal to generate acoustic bursts; areceiver to sense a response of the acoustic transducer to echoes ofeach acoustic burst; a processing circuit coupled to the receiver toconvert said received response into output data; and an interface toconvey said output data over the communication bus, wherein at least oneof the processing circuit and the microcontroller is configured to:correlate said response with a pulse pattern to obtain a correlatedresponse; distinguish peak areas from non-peak areas in said correlatedresponse; derive a noise level in a portion of said correlated responseusing only the non-peak areas within said portion; calculate a signal tonoise ratio (SNR) for a peak signal within the portion as a ratio of apeak value for the peak signal to said the noise level; and accept thepeak signal as an echo only if the SNR for said peak signal exceeds apredetermined threshold.
 11. The park assist control system as claimedin claim 10, wherein the processing circuit of the controller isconfigured to calculate said SNR ratio, and wherein the microcontrolleris configured to process raw data transmitted via the communication busfrom the controller.
 12. The park assist control system of claim 11,wherein the raw data excludes the non-peak areas.
 13. The park assistcontrol system of claim 10, wherein the microcontroller is configured todistinguish peak areas from non-peak areas in the correlated responseusing a Continuous False Alarm Rate (CFAR) threshold.
 14. The parkassist control system of claim 13, wherein the microcontroller furtherdetermines a derivative signal from the correlated response, and acceptsthe peak signal as an echo only if the derivative signal correspondingto said peak signal exceeds a derivative threshold.
 15. A method ofoperating a piezoelectric-based sensor, the method comprising: driving apiezoelectric transducer to generate a burst of acoustic energy;obtaining a response from the piezoelectric transducer; correlating saidresponse relative to said driving signal to obtain a correlatedresponse; distinguish peak areas from non-peak areas in said correlatedresponse; deriving a noise level in a portion of said correlatedresponse using only the non-peak areas within said portion; calculatinga signal to noise ratio (SNR) for a peak signal within the portion as aratio of a peak value of for the peak signal to the noise level; andaccepting the peak signal as an echo only if the SNR for said peaksignal exceeds a predetermined threshold.
 16. The method of claim 15,further comprising: determining a derivative signal from the correlatedresponse; accepting the peak signal as an echo only if the derivativesignal corresponding to said peak signal exceeds a derivative threshold.17. The method of claim 15, wherein said distinguishing the peak areasfrom non-peak areas comprises calculating a CFAR threshold using aContinuous False Alarm Rate (CFAR) algorithm, and comparing a magnitudeof the correlated response with said CFAR threshold.
 18. The method ofclaim 15, further comprising reporting the peak signal as a groundreflection if the SNR falls below the predetermined threshold.
 19. Acontroller for an acoustic transducer, the controller comprising: atransmitter drive the acoustic transducer with a driving signal togenerate acoustic bursts; a receiver to sense a response of the acoustictransducer to echoes of each acoustic burst; a processing circuitcoupled to the transmitter and to the receiver, the processing circuitconfigured to convert said received response into output data by:correlating said response to said driving signal to obtain a correlatedresponse; distinguishing peak areas from non-peak areas in saidcorrelated response; using the non-peak areas in a portion of thecorrelated response to derive a noise level; calculating a signal tonoise ratio (SNR) for a peak signal within the portion as a ratio of apeak value for the peak signal to the noise level; and identifying thepeak signal as a ground reflection if the SNR falls below apredetermined threshold.
 20. The controller of claim 19, wherein saiddistinguishing the peak areas from non-peak areas comprises calculatinga CFAR threshold using a Continuous False Alarm Rate (CFAR) algorithm,and comparing a magnitude of the correlated response with said CFARthreshold.